Beyond catharsis: the nuanced emotion of patient storytellers in an educational role
Bibliographic record
Abstract
CONTEXT: As health care organisations seek to cultivate patient and family-centred care, patient storytelling has emerged as a valued educational resource. However, repeatedly harnessing patient perspectives to educate health care professionals may have consequences. We need robust insight into what it means to be a patient storyteller in order to ensure ethical and appropriate engagement with patients as an educational resource. METHODS: Constructivist grounded theory was used to explore the experience of patients involved in a storytelling curriculum as part of hospital staff continuing education. All 33 storytellers were invited by e-mail to participate in the study. Twenty-six storytellers responded to the invitation, and 25 could be scheduled to participate. Using theoretical sampling, semi-structured interviews were conducted and analysed in a process that was inductive, iterative and comparative. RESULTS: Participants described the central role of emotions in their storytelling experience, which varied from 1 to 25 tellings over a period of 1 month to 2 years. These emotions were shaped by the passage of time, repetition of storytelling and audience acknowledgement. However, emotion remained unpredictable and had lingering implications for storytellers' vulnerability. CONCLUSION: The multiple storytelling experiences of our participants and ongoing educational nature of their role provides unique insight into how emotions ebb and flow across tellings, how emotions can be both a surprise and a rhetorical strategy, and how emotions are influenced by audience acknowledgement. These findings contribute to an emerging conversation regarding the power and politics of selecting and using storytellers for organisational purpose. Implications include how we support patient storytellers in educational roles and how we can sustainably integrate patient storytelling into health professional education.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".